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Corrosion cracking prediction updating of deteriorating RC structures using inspection information

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  • Suo, Qinghui
  • Stewart, Mark G.

Abstract

It is well known that the corrosion-induced cracking of reinforced concrete (RC) structures varies in time and space due to the inherent spatial variability of concrete cover, concrete strength, surface chloride concentration and other material, environmental and dimensional properties. A model for predicting the likelihood and extent of RC corrosion-induced cracking considering spatial variability is reviewed. The uncertainties of predictions can be reduced by the effective use of information obtained from visual inspections regarding structural performance, such as cracking proportion and crack width. The paper uses a spatial time-dependent reliability analysis combined with visual inspection data to predict the likelihood and extent of RC corrosion-induced cracking. In this study, RC slabs and beams are used to illustrate the influence of inspection information updating on the future likelihood and extent of corrosion-induced cracking. Concrete strength, concrete cover and the surface chloride concentrations are modelled as spatial variables. Monte-Carlo simulation is employed to calculate the updated cracking proportions. The analysis considers various inspection scenarios which include different inspection intervals, inspection times, cracking proportion and crack width. It was found that the occurrence or observance of cracking changes the future cracking prediction significantly.

Suggested Citation

  • Suo, Qinghui & Stewart, Mark G., 2009. "Corrosion cracking prediction updating of deteriorating RC structures using inspection information," Reliability Engineering and System Safety, Elsevier, vol. 94(8), pages 1340-1348.
    • Handle: RePEc:eee:reensy:v:94:y:2009:i:8:p:1340-1348
    DOI: 10.1016/j.ress.2009.02.011
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    References listed on IDEAS

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    1. Stewart, Mark G. & Al-Harthy, Ali, 2008. "Pitting corrosion and structural reliability of corroding RC structures: Experimental data and probabilistic analysis," Reliability Engineering and System Safety, Elsevier, vol. 93(3), pages 373-382.
    2. Kallen, M.J. & van Noortwijk, J.M., 2005. "Optimal maintenance decisions under imperfect inspection," Reliability Engineering and System Safety, Elsevier, vol. 90(2), pages 177-185.
    3. Sudret, B., 2008. "Probabilistic models for the extent of damage in degrading reinforced concrete structures," Reliability Engineering and System Safety, Elsevier, vol. 93(3), pages 410-422.
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    Cited by:

    1. Gayathri, P. & Umesh, K. & Ganguli, R., 2010. "Effect of matrix cracking and material uncertainty on composite plates," Reliability Engineering and System Safety, Elsevier, vol. 95(7), pages 716-728.
    2. Xingji Zhu & Zaixian Chen & Hao Wang & Yabin Chen & Longjun Xu, 2018. "Probabilistic Generalization of a Comprehensive Model for the Deterioration Prediction of RC Structure under Extreme Corrosion Environments," Sustainability, MDPI, vol. 10(9), pages 1-17, August.
    3. Ching, Jianye & Leu, Sou-Sen, 2009. "Bayesian updating of reliability of civil infrastructure facilities based on condition-state data and fault-tree model," Reliability Engineering and System Safety, Elsevier, vol. 94(12), pages 1962-1974.

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